--- title: "Physics and Astronomy — papers — Elamur Research" description: "Physics and Astronomy: 25 papers of the Elamur Research library, the most cited first — our summary of each, its ideas, references and who…" canonical: "https://research.elamur.ai/free/en/shelves/physics-and-astronomy/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/physics-and-astronomy/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / Physics and Astronomy # ⚛️ Physics and Astronomy 25 papers · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Physics from particles to galaxies: quantum, condensed matter, optics, astronomy. ## Subfields The sub-shelves of Physics and Astronomy, the most papers first, with the two OpenAlex topics most of their papers here are on. 1. [**Statistical and Nonlinear Physics**Complex Network Analysis Techniques · Opinion Dynamics and Social Influence*22 papers*](https://md.research.elamur.ai/free/en/shelves/physics-and-astronomy/statistical-and-nonlinear-physics/) 2. [**Atomic and Molecular Physics, and Optics**Advanced Chemical Physics Studies · Color Science and Applications*2 papers*](https://md.research.elamur.ai/free/en/shelves/physics-and-astronomy/atomic-and-molecular-physics-and-optics/) 3. [**Astronomy and Astrophysics**Astro and Planetary Science · Planetary Science and Exploration*1 paper*](https://md.research.elamur.ai/free/en/shelves/physics-and-astronomy/astronomy-and-astrophysics/) ## Papers (25) 1. [**Graph Attention Networks**Petar Veličkovic, Guillem Cucurull, Arantxa Casanova, et al.*2017 · 9,000 citations*](https://md.research.elamur.ai/free/en/papers/veli-vckovic-2017-graph-attention-networks/) 2. [**Semi-Supervised Classification with Graph Convolutional Networks**Thomas N. Kipf, Max Welling*2016 · 8,826 citations*](https://md.research.elamur.ai/free/en/papers/kipf-2016-semi-supervised-classification-graph-convolutional/) 3. [**Inductive Representation Learning on Large Graphs**William L. Hamilton, Rex Ying, Jure Leskovec*2017 · 4,696 citations*](https://md.research.elamur.ai/free/en/papers/hamilton-2017-inductive-representation-learning-large-graphs/) 4. [**Neural Message Passing for Quantum Chemistry**Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, et al.*2017 · 3,703 citations*](https://md.research.elamur.ai/free/en/papers/gilmer-2017-neural-message-passing-quantum-chemistry/) 5. [**Determining the Sentiment of Opinions**Soo-Min Kim, Eduard Hovy*2004 · 1,679 citations*](https://md.research.elamur.ai/free/en/papers/kim-2004-determining-sentiment-opinions/) 6. [**Score-Based Generative Modeling through Stochastic Differential Equations**Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, et al.*2020 · 1,530 citations*](https://md.research.elamur.ai/free/en/papers/song-2020-score-based-generative-modeling-through/) 7. [**Generative Modeling by Estimating Gradients of the Data Distribution**Yang Song, Stefano Ermon*2019 · 1,159 citations*](https://md.research.elamur.ai/free/en/papers/song-2019-generative-modeling-estimating-gradients-data/) 8. [**Out of One, Many: Using Language Models to Simulate Human Samples**Lisa P. Argyle, Ethan C. Busby, Nancy Fulda, et al.*2022 · 944 citations*](https://md.research.elamur.ai/free/en/papers/argyle-2022-out-one-many-using-language/) 9. [**Rumor has it: Identifying Misinformation in Microblogs**Vahed Qazvinian, Emily Rosengren, Dragomir R. Radev, et al.*2011 · 771 citations*](https://md.research.elamur.ai/free/en/papers/qazvinian-2011-rumor-has-it-identifying-misinformation/) 10. [**Detect Rumors in Microblog Posts Using Propagation Structure via Kernel Learning**Jing Ma, Wei Gao, Kam-Fai Wong*2017 · 714 citations*](https://md.research.elamur.ai/free/en/papers/ma-2017-detect-rumors-microblog-posts-propagation/) 11. [**Rumor Detection on Twitter with Tree-structured Recursive Neural Networks**Jing Ma, Wei Gao, Kam-Fai Wong*2018 · 708 citations*](https://md.research.elamur.ai/free/en/papers/ma-2018-rumor-detection-twitter-tree-structured/) 12. [**GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media**Yi-Ju Lu, Cheng-Te Li*2020 · 468 citations*](https://md.research.elamur.ai/free/en/papers/lu-2020-gcan-graph-aware-co-attention/) 13. [**Flow Matching for Generative Modeling**Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, et al.*2022 · 397 citations*](https://md.research.elamur.ai/free/en/papers/lipman-2022-flow-matching-generative-modeling/) 14. [**Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow**Xingchao Liu, Chengyue Gong, Qiang Liu*2022 · 254 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-flow-straight-fast-learning-generate/) 15. [**Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color**Mostafa Abdou, Artur Kulmizev, Daniel Hershcovich, et al.*2021 · 119 citations*](https://md.research.elamur.ai/free/en/papers/abdou-2021-can-language-models-encode-perceptual/) 16. [**Supervised and Unsupervised Methods in Employing Discourse Relations for Improving Opinion Polarity Classification**Swapna Somasundaran, Galileo Namata, Janyce Wiebe, et al.*2009 · 119 citations*](https://md.research.elamur.ai/free/en/papers/somasundaran-2009-supervised-unsupervised-methods-employing-discourse/) 17. [**Chinese Whispers - an Efficient Graph Clustering Algorithm and its Application to Natural Language Processing Problems**Chris Biemann*2006 · 116 citations*](https://md.research.elamur.ai/free/en/papers/biemann-2006-chinese-whispers-efficient-graph-clustering/) 18. [**Evolution of the most common English words and phrases over the centuries**Matjaz Perc*2012 · 109 citations*](https://md.research.elamur.ai/free/en/papers/perc-2012-evolution-most-common-english-words/) 19. [**OpinionFinder: A System for Subjectivity Analysis**Theresa Wilson, Paul Hoffmann, Swapna Somasundaran, et al.*2005 · 78 citations*](https://md.research.elamur.ai/free/en/papers/wilson-2005-opinionfinder-system-subjectivity-analysis/) 20. [**Patterns in the English Language: Phonological Networks, Percolation and Assembly Models**Massimo Stella, Markus Brede*2014 · 38 citations*](https://md.research.elamur.ai/free/en/papers/stella-2014-patterns-english-language-phonological-networks/) 21. [**The Rosetta project**Jan Landsbergen*1989 · 11 citations*](https://md.research.elamur.ai/free/en/papers/landsbergen-1989-rosetta-project/) 22. [**Mental Lexicon Growth Modelling Reveals the Multiplexity of the English Language**Massimo Stella, Markus Brede*2016 · 10 citations*](https://md.research.elamur.ai/free/en/papers/stella-2016-mental-lexicon-growth-modelling-reveals/) 23. [**Multifractal analysis of sentence lengths in English literary texts**Iwona Grabska-Gradzinska, Andrzej Kulig, Jarosław Kwapien, et al.*2012 · 7 citations*](https://md.research.elamur.ai/free/en/papers/grabska-gradzinska-2012-multifractal-analysis-sentence-lengths-english/) 24. [**ARAACOM: ARAbic Algerian Corpus for Opinion Mining**Zitouni Abdelhafid, Hichem Rahab, Abdelhafid Zitouni, et al.*2017 · 6 citations*](https://md.research.elamur.ai/free/en/papers/abdelhafid-2020-araacom-arabic-algerian-corpus-opinion/) 25. [**Modeling Changing Scientific Concepts with Complex Networks: A Case Study on the Chemical Revolution**Sofia Aguilar Valdez, Stefania Degaetano-Ortlieb*2026*](https://md.research.elamur.ai/free/en/papers/valdez-2026-modeling-changing-scientific-concepts-complex/) Updated 24 October 2026 - [← previous shelf Pharmacology, Toxicology and Pharmaceutics](https://md.research.elamur.ai/free/en/shelves/pharmacology-toxicology-and-pharmaceutics/) - [next shelf → Psychology](https://md.research.elamur.ai/free/en/shelves/psychology/) - [↑ back to shelves](https://md.research.elamur.ai/free/en/shelves/)